Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method by Mouhssine EL ATILLAH, Khalid EL FAZAZY, Jamal Riffi

“… The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. …”
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Enhanced Fault Detection in Photovoltaic Panels Using CNN-Based Classification with PyQt5 Implementation by Younes Ledmaoui, Adila El Maghraoui, Mohamed El Aroussi, Rachid Saadane

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EmoFusion: An integrated machine learning model leveraging embeddings and lexicons to improve textual emotion classification by Anjali Bhardwaj, Muhammad Abulaish

“…This paper presents EmoFusion, an integrated machine learning model that improves emotion classification in textual data by integrating pre-trained word embeddings and emotion lexicons. …”
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Classification of the Tasks of Local Governmental Units in Poland in the Light of Fundamental Legal Acts — Discussion of Selected Aspects by Marta Mulawa

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A Novel Neural Network Framework for Automatic Modulation Classification via Hankelization-Based Signal Transformation by Jung-Hwan Kim, Jong-Ho Lee, Oh-Soon Shin, Woong-Hee Lee

“…Automatic modulation classification (AMC) is a fundamental technique in wireless communication systems, as it enables the identification of modulation schemes at the receiver without prior knowledge, thereby promoting efficient spectrum utilization. …”
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Designing a hybrid stack ensemble model to enhance sepsis classification using data triangulation approach by Safiya Parvin A․, Saleena B․

“…Sepsis is a major health issue affecting newborns, often caused by factors such as premature birth, birth asphyxia, pneumonia, and meningitis. …”
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Data Augmentation For Sorani Kurdish News Headline Classification Using Back-Translation And Deep Learning Model by Soran Badawi

“…With the increase in the volume of news articles and headlines being generated, it is becoming more difficult for individuals to keep up with the latest developments and find relevant news articles in the Kurdish language. To address this issue, this paper proposes a novel data augmentation approach for improving the performance of Kurdish news headline classification using back-translation and a proposed deep learning Bidirectional Long Short-Term Memory (BiLSTM) model. …”
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Review of therapeutic agents for burns pruritus and protocols for management in adult and paediatric patients using the GRADE classification by Goutos Ioannis, Clarke Maria, Upson Clara, Richardson Patricia, Ghosh Sudip

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Binary and multiclass malware classification of windows portable executable using classic machine learning and deep learning by Moeiz Miraoui, Mohamed Ben Belgacem

“…Most previous works focus on binary classification, limited number of ML algorithms and even a single dataset. …”
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TI-RADS CLASSIFICATION SYSTEM AND ITS FIRST APPLICATION IN THE ULTRASOUND DIAGNOSIS DEPARTMENT IN THE MULTI-SPECIALITY HOSPITAL by A. A. Kvasova, A. N. Katrich

“…The most common classification system is TI-RADS.Objective. To evaluate the TI-RADS classification efficacy for the thyroid gland nodular tumor diagnosis in a multispecialty hospital.Materials and Methods. …”
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A Multi-Source Data-Driven Analysis of Building Functional Classification and Its Relationship with Population Distribution by Dongfeng Ren, Xin Qiu, Zehua An

“…Existing research mainly focuses on the relationship between land functions and population distribution at the macro scale, while neglecting the finer-grained, micro-scale impact of building functionality on population distribution. To address this issue, this study integrates multi-source geospatial and spatio-temporal big data and employs the XGBoost algorithm to classify buildings into five functional categories: residential, commercial, industrial, public service, and landscape. …”
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GLI-Net: A global and local interaction network for accurate classification of gastrointestinal diseases in endoscopic images by Yuansen Zhang, Mengxiao Zhuang, Wenjun Chen, Xiaoqiu Wu, Qingqing Song

“…However, current methods face challenges in effectively integrating both global and local features, which limits their ability to capture both broad semantic information and subtle lesion details, ultimately affecting classification performance. To address this issue, this study introduces a novel deep learning framework, the Global and Local Interaction Network (GLI-Net). …”
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Smartphone-Based Deep Learning System for Detecting Ractopamine-Fed Pork Using Visual Classification Techniques by Hong-Dar Lin, Mao-Quan He, Chou-Hsien Lin

“…Given the high demand for pork, consumers need a reliable way to verify meat authenticity. To address this issue, this study proposes a smartphone-based visual detection system for meat cut and pork origin classification, extending to ractopamine detection. …”
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Semantic consistency enhancement and contribution-driven network for partial multi-view incomplete multi-label classification by Yishan Jiang, Lian Zhao, Zhixian Jiang, Yinghao Ye, Xiaohuan Lu

“…Currently, some frameworks have been introduced to address the complex issue of partial multi-view incomplete multi-label classification, but they frequently overlook the impact of view quality on the learning of semantic information. …”
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A novel three-way distance-based fuzzy large margin distribution machine for imbalance classification by Li Liu, Jinrui Guo, Ziqi Yin, Rui Chen, Guojun Huang

“…Abstract Class imbalance is a prevalent issue in practical applications, which poses significant challenges for classifiers. …”
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Domain knowledge-infused pre-trained deep learning models for efficient white blood cell classification by P. Jeneessha, Vinoth Kumar Balasubramanian

“…Though a lot of research has been taken up to develop deep learning models for efficient classification of WBCs, there is still scope for improvement to support the data insufficiency issue in medical data sets. …”
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A stochastic optimization method for economic microgrid operation based on "source-load operation" mode classification by ZHOU Hang, MA Lihong, LI Zhongzhong, WANG Haisheng, LI Sifan, ZHANG Changjun, FU Linbei

“…The volatility of renewable energy output and the randomness of user-side electricity consumption behavior have led to increasing source-load uncertainties， posing significant operational risks to microgrids. To address this issue， an economic operation decision-making method for microgrids based on source-load operation mode classification is proposed to achieve economic operation under uncertain conditions. …”
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Instance-level medical image classification for text-based retrieval in a medical data integration center by Ka Yung Cheng, Markus Lange-Hegermann, Jan-Bernd Hövener, Björn Schreiweis

“…However, some images have incorrect or missing annotations, which creates challenges in searching and integrating data centrally. To address this issue, accurate and meaningful descriptors are needed for indexing fields, enabling users to efficiently search for desired images and integrate them with international standards.This paper aims to provide concise annotation for missing or incorrectly indexed fields, incorporating essential instance-level information such as radiology modalities (e.g., X-rays), anatomical regions (e.g., chest), and body orientations (e.g., lateral) using a Deep Learning classification model - ResNet50. …”
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Towards Efficient Object Detection in Large-Scale UAV Aerial Imagery via Multi-Task Classification by Shuo Zhuang, Yongxing Hou, Di Wang

“…However, the extensive object-free background areas in large-scale aerial imagery reduce detection efficiency. To address this issue, we propose an efficient object detection approach for large-scale UAV aerial imagery via multi-task classification. …”
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Fine Recognition of MEO SAR Ship Targets Based on a Multi-Level Focusing-Classification Strategy by Zhaohong Li, Wei Yang, Can Su, Hongcheng Zeng, Yamin Wang, Jiayi Guo, Huaping Xu

“…However, due to the huge computational load required for imaging processing and the severe defocusing caused by ship motions, traditional ship recognition conducted in focused image domains cannot process MEO SAR data efficiently. To address this issue, a multi-level focusing-classification strategy for MEO SAR ship recognition is proposed, which is applied to the range-compressed ship data domain. …”
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